Image analyzing apparatus and non-transitory storage medium storing instructions executable by the image analyzing apparatus

ABSTRACT

An image analyzing apparatus includes a controller. In a first analyzing process, the controller performs: sequentially identifying line pixel groups from a first side toward a second side in a first direction; when identifying an m1th line pixel group, creating m1th first distance information corresponding to the m1th line pixel group based on m1−1th pixel information corresponding to an m1−1th line pixel group and on m1−1th first distance information corresponding to the m1−1th line pixel group; and when the m1th line pixel group contains a first subject group constituted by at least one first-type pixel contiguous to each other in the second direction each as the first-type pixel, determining, based on the created m1th first distance information, whether the first-type pixel not contiguous to the first subject group is present in a first region surrounding the first subject group.

CROSS REFERENCE TO RELATED APPLICATION

The present application claims priority from Japanese Patent ApplicationNo. 2016-175442, which was filed on Sep. 8, 2016, the disclosure ofwhich is herein incorporated by reference in its entirety.

BACKGROUND

The following disclosure relates to an image analyzing apparatusconfigured to execute an analyzing process using read image data createdby reading a document and to a non-transitory storage medium storing aplurality of instructions executable by a computer of the imageanalyzing apparatus.

There is known a noise remover for removing a noise from image data. Oneexample of the noise is a fine black point (speck). The noise removeridentifies a black pixel in the image data as a notable point. Whenblack pixels more than or equal in number to a predetermined number arepresent in a region located within a distance corresponding to, e.g.,three pixels from the notable point, the noise remover determines thatthe notable point is not a noise. When black pixels more than or equalin number to the predetermined number are absent in the region, thenoise remover determines that the notable point is a noise.

SUMMARY

Incidentally, image data normally contains, a plurality of line pixelgroups arranged in a first direction, e.g., an up and down direction.Each of the line pixel groups is constituted by a plurality of pixelsarranged in a second direction orthogonal to the first direction. Oneexample of the second direction is a right and left direction. In mostcases, the line pixel groups are sequentially identified from a firstside to a second side in the first direction, and a processing isexecuted for each of the line pixel groups. In the above-describedtechnique, in order to determine whether each notable point contained ina certain line pixel group is a noise, the noise remover has to checknot only the certain line pixel group but also three line pixel groupslocated on an upper side of the certain line pixel group and three linepixel groups located on a lower side of the certain line pixel group.Thus, the noise remover determines whether the notable point is a noise,in a state in which the seven line pixel groups are stored in a workingarea of a memory.

Accordingly, an aspect of the disclosure relates to a technique forachieving a small memory usage amount when determining whether apredetermined region located near a subject group contains a first-typepixel not contiguous to the subject group.

In one aspect of the disclosure, an image analyzing apparatus, includinga controller configured to perform: acquiring read image data created byreading of a document; executing a first analyzing process based on theacquired read image data; and executing a first process based on aresult of the first analyzing process. The controller is configured to,in the first analyzing process, perform: sequentially identifying aplurality of line pixel groups from a first side toward a second side ina first direction, wherein the plurality of line pixel groups arearranged in the first direction, wherein each of the plurality of linepixel groups includes a plurality of pixels arranged in a seconddirection orthogonal to the first direction, wherein each of theplurality of pixels is one of a first-type pixel and a second-typepixel, wherein the first-type pixel is a pixel of a first type, and thesecond-type pixel is a pixel of a second type; in a case where an m1thline pixel group among the plurality of line pixel groups, creating m1thfirst distance information corresponding to the m1th line pixel groupbased on (m1−1)th pixel information corresponding to an (m1−1)th linepixel group among the plurality of line pixel groups and on (m1−1)thfirst distance information corresponding to the (m1−1)th line pixelgroup, wherein the pixel information for each of the plurality of linepixel groups indicates that each of the plurality of pixels constitutingsaid each of the plurality of line pixel groups is one of the first-typepixel and the second-type pixel, wherein the first distance informationfor each of the plurality of line pixel groups indicates a distancebetween each pixel of the plurality of pixels constituting said each ofthe plurality of line pixel groups and the first-type pixel located onthe first side of said each pixel and nearest to said each pixel,wherein m1 is an integer greater than or equal to two; and in a casewhere the m1th line pixel group includes a first subject groupconstituted by at least one first-type pixel contiguous to each other inthe second direction each as the first-type pixel, determining, based onthe created m1th first distance information, whether the first-typepixel not contiguous to the first subject group is present in a firstregion surrounding the first subject group. The controller is configuredto, based on the result of the first analyzing process, execute thefirst process for an object including the first subject group andconstituted by the at least one first-type pixel contiguous to eachother.

Another aspect of the disclosure relates to a non-transitory storagemedium storing a plurality of instructions executable by a computer ofan image analyzing apparatus. The plurality of instructions, whenexecuted by the computer, causing the image analyzing apparatus toperform: acquiring read image data created by reading of a document;executing a first analyzing process based on the acquired read imagedata; and executing a first process based on a result of the firstanalyzing process. When executed by the computer, the plurality ofinstructions cause the image analyzing apparatus to, in the firstanalyzing process, perform: sequentially identifying a plurality of linepixel groups from a first side toward a second side in a firstdirection, wherein the plurality of line pixel groups are arranged inthe first direction, wherein each of the plurality of line pixel groupsincludes a plurality of pixels arranged in a second direction orthogonalto the first direction, wherein each of the plurality of pixels is oneof a first-type pixel and a second-type pixel, wherein the first-typepixel is a pixel of a first type, and the second-type pixel is a pixelof a second type; in a case where an m1th line pixel group among theplurality of line pixel groups, creating m1th first distance informationcorresponding to the m1th line pixel group based on (m1−1)th pixelinformation corresponding to an (m1−1)th line pixel group among theplurality of line pixel groups and on (m1−1)th first distanceinformation corresponding to the (m1−1)th line pixel group, wherein thepixel information for each of the plurality of line pixel groupsindicates that each of the plurality of pixels constituting said each ofthe plurality of line pixel groups is one of the first-type pixel andthe second-type pixel, wherein the first distance information for eachof the plurality of line pixel groups indicates a distance between eachpixel of the plurality of pixels constituting said each of the pluralityof line pixel groups and the first-type pixel located on the first sideof said each pixel and nearest to said each pixel, wherein m1 is aninteger greater than or equal to two; and in a case where the m1th linepixel group includes a first subject group constituted by at least onefirst-type pixel contiguous to each other in the second direction eachas the first-type pixel, determining, based on the created m1th firstdistance information, whether the first-type pixel not contiguous to thefirst subject group is present in a first region surrounding the firstsubject group. The controller is configured to, based on the result ofthe first analyzing process, execute the first process for an objectincluding the first subject group and constituted by the at least onefirst-type pixel contiguous to each other.

BRIEF DESCRIPTION OF THE DRAWINGS

The objects, features, advantages, and technical and industrialsignificance of the present disclosure will be better understood byreading the following detailed description of the embodiments, whenconsidered in connection with the accompanying drawings, in which:

FIG. 1 is a schematic view of a hardware configuration in oneembodiment;

FIG. 2 is a flow chart of a process executed by a scanner;

FIG. 3 is a flow chart of an analyzing process;

FIG. 4 is a flow chart of a process for creating object data;

FIG. 5 is a flow chart of a process for updating the object data;

FIG. 6 is a view for explaining x-direction information, y-directioninformation, and the object data;

FIG. 7 is a view for explaining first and second analyzing processes;

FIG. 8 is a view illustrating results of the first and second analyzingprocesses;

FIG. 9 is a view for explaining a comparative example and a secondembodiment; and

FIG. 10 is a view for explaining a third embodiment.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Hereinafter, there will be described embodiments by reference to thedrawings.

First Embodiment

First, a configuration of a scanner 10 according to one embodiment willbe described with reference to FIG. 1. The scanner 10 is communicablyconnected to a personal computer (PC) 50 over a local area network(LAN). The scanner 10 includes an operation device 12, a display 14, anetwork interface 16, a scan engine 18, and a controller 30. Theoperation device 12 includes a plurality of keys. A user operates theoperation device 12 to input various instructions to the scanner 10. Thedisplay 14 is configured to display various kinds of information. Thedisplay 14 has a touch screen. That is, the display 14 also functions asan operation device. The network interface 16 is connected to the LAN.The scan engine 18 includes a scanning mechanism such as a CCD and aCID.

The controller 30 includes a CPU 32 and a memory 34. The memory 34includes a read only memory (ROM) and a random access memory (RAM). TheCPU 32 is configured to execute various processings according to aprogram 36 stored in the memory 34. One example of the processings is aprocessing illustrated in FIG. 2 which will be described below. The RAMof the memory 34 has a working area 38 for temporarily storinginformation during processing.

The CPU 32 receives a scan instruction 100 from the PC 50 via thenetwork interface 16. The scan instruction 100 includes reading settingssuch as a reading resolution and a size of a document. The CPU 32controls the scan engine 18 to read a document using the readingsettings and acquires scan data from the scan engine 18. A scan image110 represented based on the scan data include: an object 112representing a photograph; and objects 116, 118 respectivelyrepresenting characters, for example.

In the case where a dust particle adheres to a document or a transparentplate, not illustrated, of the scanner 10 on which the document isplaced, for example, the scan image 110 may include an object 114representing the dust particle (hereinafter referred to as “isolatedpoint”). In the present embodiment, the CPU 32 executes a correctingprocess for removing the isolated point 114 and creates corrected imagedata 130 representing a corrected image 120. The CPU 32 transmits thecorrected image data 130 to the PC 50 via the network interface 16.These processings enable the CPU 32 to send the PC 50 the image data 130representing the image 120 with a higher image quality.

There will be next explained, with reference to the flow chart in FIG.2, a scanner process that is executed by the CPU 32 according to theprogram 36 when the scan instruction 100 is input.

This flow begins with S10 at which the CPU 32 controls the scan engine18 to read a document and receives scan data from the scan engine 18.The scan data is constituted by: pixels arranged in an x direction(e.g., the right and left direction of the scan image 110 in FIG. 1);and pixels arranged in a y direction (e.g., the up and down direction ofthe scan image 110 in FIG. 1). In other words, the scan data isconstituted by a plurality of reading lines arranged in the y direction.Each of the reading lines is constituted by a plurality of pixelsarranged in the x direction. Each of the pixels has a pixel value thatis one of 256 gray levels (0-255). Specifically, the pixel value isrepresented by an R value, a G value, and a B value. In the presentembodiment, it is assumed that the document is read at a readingresolution of 100 dpi.

More specifically, the CPU 32 at S10 sequentially acquires the readinglines from the scan engine 18. Each time when the CPU 32 acquires onereading line, the CPU 32 compresses the reading line to create acompressed line and stores the created compressed line into the workingarea 38 in the memory 34. As a result, compressed scan data constitutedby the compressed lines is stored into the working area 38. Since thescan data is stored in the working area 38 in a state in which the scandata is compressed, an amount of usage of the working area 38 is small.

At S20, the CPU 32 executes a first analyzing process using thecompressed scan data. In the first analyzing process, the reading linesconstituting the scan data are sequentially analyzed from the upper sidetoward the lower side in the y direction.

At S30, the CPU 32 executes a second analyzing process using thecompressed scan data. In the second analyzing process, the reading linesconstituting the scan data are sequentially analyzed from the lower sidetoward the upper side in the y direction.

At S40, the CPU 32 uses a result of the first analyzing process at S20and a result of the second analyzing process at S30 to execute anidentification process for identifying the isolated point.

At S50, the CPU 32 corrects each of pixels which represents the isolatedpoint identified at S40 in the compressed scan data, to a pixelrepresenting a background color of the scan image 110 (white in thepresent embodiment). As a result, the CPU 32 creates the corrected imagedata 130 representing the corrected image 120. Though not illustrated,the CPU 32 transmits the corrected image data 130 to the PC 50. When theprocess at S50 is finished, the flow in FIG. 2 ends.

There will be next explained, with reference to FIG. 3, the firstanalyzing process executed at S20 in FIG. 2. At S100, the CPU 32 sets apointer m to “0” to identify the mth reading line, i.e., the 0th readingline. The pointer m indicates a reading line to be processed. In thefirst analyzing process, as described above, the reading linesconstituting the scan data are sequentially analyzed from the upper sidetoward the lower side in the y direction. Accordingly, the 0th readingline is an uppermost one of the reading lines. More specifically, theCPU 32 at S100 decompresses an uppermost one of the compressed linesconstituting the compressed scan data and writes the 0th reading line(i.e., the pixels arranged in the x direction) into the working area 38.In particular, before starting the processing at S100, the CPU 32allocates a first working area and a second working area in the workingarea 38. The CPU 32 writes the 0th reading line into the first workingarea. Information in the first working area is sequentially deleted in aperiod in which the processing is executed for each line. Information inthe second working area is not deleted in the period in which theprocessing is executed for each line. The information in the secondworking area is deleted after the completion of the process at S50 whichwill be described below.

At S102, the CPU 32 executes an intensity-value conversion processingfor the mth reading line. Specifically, for each of the pixelsconstituting the mth reading line, the CPU 32 converts the pixel valuerepresented by the pixel (i.e., the R value, the G value, and the Bvalue) to an intensity value (i.e., a Y value) according to theexpression “Y=0.299×R+0.587×G+0.114×B” and creates a new pixelrepresenting an intensity value as one of the 256 gray levels (0-255).The CPU 32 then writes an intensity line into the first working area inthe working area 38. The intensity line is constituted by a plurality ofpixels each representing an intensity value. In the present embodiment,the document read by the scanner 10 has a background of a white color(i.e., R=G=B=255). Thus, an intensity value representing the backgroundof the document (i.e., a Y value) is normally 255, and an intensityvalue representing each area on the document which differs from thebackground is normally a value less than 255. When writing the mthintensity line into the first working area at S102, the CPU 32 deletesthe mth reading line from the first working area.

At S104, the CPU 32 executes a binary conversion processing for theintensity line created at S102. Specifically, for each of the pixelsconstituting the intensity line, the CPU 32 converts the intensity valuerepresented by the pixel, into “1” or “0” and creates a new pixelrepresenting “1” or “0”. More specifically, the CPU 32 creates a pixelrepresenting “1” when the intensity value is less than or equal to apredetermined threshold value (e.g., 200), and the CPU 32 creates apixel representing “0” when the intensity value is greater than thethreshold value. That is, the pixel representing the background of thedocument is expressed as “0”, and each pixel representing an objectdifferent from the background of the document is expressed as “1”. TheCPU 32 then writes a binary line into the first working area. The binaryline is constituted by the pixels each representing “0” or “1”. In thefollowing description, the pixel representing “1” and the pixelrepresenting “0” are respectively referred to as “ON pixel” and “OFFpixel”. The CPU 32 deletes the mth intensity line from the first workingarea when writing the mth binary line into the first working area atS104.

At S110, the CPU 32 uses the mth binary line created at S104 to writethe mth x-direction information into the first working area. Thex-direction information represents arrangement of the ON pixels and theOFF pixels contained in the mth binary line. The x-direction informationis expressed as numbers equal in number to the number of pixels in thebinary line. That is, the x-direction information is expressed as asequence of the numbers. For example, in the case where the mth binaryline contains one or more ON pixels contiguous to each other, the CPU 32assigns “1”, “2”, “3”, and so on to the respective ON pixels as thenumbers respectively corresponding to the ON pixels, in order in theleft direction from a rightmost one of the ON pixels. For example, inthe case where the mth binary line contains one or more OFF pixelscontiguous to each other, the CPU 32 assings “−1”, “−2”, “−3”, and so onto the respective OFF pixels as the numbers respectively correspondingto the OFF pixels, in order in the left direction from a rightmost oneof the OFF pixels.

FIG. 6 illustrates one example of a plurality of the binary lines(eleven binary lines) arranged in the y direction. In reality, aplurality of the binary lines are never stored in the first working areaat the same time, and only one binary line is stored in the firstworking area. In FIG. 6, one binary line is constituted by 26 pixelsarranged in the x direction, the rectangular shapes represents therespective ON pixels, and a region containing no rectangular shaperepresents the OFF pixels. It is noted that each value in therectangular shape represents a label value which will be explainedbelow. For example, the 0th binary line corresponding to “y=0” isconstituted only by the 26 OFF pixels. In this case, the CPU 32 createsa sequence of the numbers “−1, −2, . . . , 26” as the x-directioninformation in order from the right side toward the left side. Also, thefirst binary line corresponding to “y=1” is constituted by three OFFpixels 200 (an OFF pixel group 200), three ON pixels 202 (an ON pixelgroup 202), nine OFF pixels 204 (an OFF pixel group 204), six ON pixels206 (an ON pixel group 206), and five OFF pixels 208 (an OFF pixel group208) in order from the right side toward the left side. In this case,the CPU 32 creates a sequence of the numbers “−1, −2, −3, 1, 2, 3, −1,−2, . . . , −9, 1, 2, . . . , 6, −1, −2, . . . , 5” as the x-directioninformation in order from the right side toward the left side.

The CPU 32 deletes the mth binary line from the first working area whenwriting the mth x-direction information into the first working area atS110 in FIG. 3. That is, the binary line stored in the first workingarea is deleted from the first working area before the next binary lineis written into the first working area. As a result, the first workingarea never stores two binary lines at the same time, the CPU 32 executesprocessings with a small memory usage amount. In a modification, the mthbinary line may be written into the first working area in a state inwhich the m−1th binary line is stored in the first working area. The CPU32 may delete the m−1th binary line from the first working area whenwriting the mth x-direction information into the first working area atS110. That is, the binary line stored in the first working area may bedeleted from the first working area after the next binary line iswritten into the first working area.

At S112, the CPU 32 uses the m−1th x-direction information and the m−1thy-direction information to write the mth y-direction information intothe first working area. The y-direction information represents, for eachof the pixels constituting the mth binary line, a distance between thepixel and the ON pixel located nearest to the pixel among the ON pixelslocated on an upper side of the pixel in the y direction. That is, they-direction information represents the number of pixels between thepixel and the nearest ON pixel. The y-direction information is expressedas numbers equal in number to the number of pixels in the binary line.That is, the y-direction information is expressed as a sequence of thenumbers. In the following description, one pixel contained in the mthbinary line will be referred to as “notable pixel”, and a pixelcontiguous to the notable pixel in the m−1th binary line (i.e., a pixellocated just on the upper side of the notable pixel) will be referred toas “reference pixel”. The CPU 32 first reads the number corresponding tothe reference pixel (hereinafter referred to as “first number”), fromthe m−1th x-direction information. In the case where the first number isa positive value, the reference pixel as the ON pixel is contiguous tothe notable pixel, and the distance between the notable pixel and the ONpixel located nearest to the notable pixel among the ON pixels locatedon an upper side of the pixel is zero. Thus, the CPU 32 assigns “0” tothe notable pixel in the mth y-direction information. In the case wherethe first number is a negative value, the reference pixel as the OFFpixel is contiguous to the notable pixel. In this case, the CPU 32 readsthe number corresponding to the reference pixel (hereinafter referred toas “second number”) from the m−1th y-direction information. In the casewhere the second number is “−1”, there is no ON pixel on an upper sideof the notable pixel. Thus, the CPU 32 assigns “−1” to the notable pixelin the mth y-direction information. In the case where the second numberis greater than or equal to zero, there is an ON pixel located on anupper side of the notable pixel and not contiguous to the notable pixel.Thus, the CPU 32 assigns a value obtained by adding one to the secondnumber, to the notable pixel in the mth y-direction information.

For example, when the CPU 32 creates the 0th y-direction information(m=0) indicated by “(y=0)” in FIG. 6, no m−1th x-direction informationand no m−1th y-direction information exist. In this case, the CPU 32creates the predetermined sequence of the numbers “−1, −1, . . . , −1”as the 0th y-direction information. When the CPU 32 creates the firsty-direction information indicated by “(y=1)”, each of the numbersrespectively corresponding to all the reference pixels is a negativevalue in the 0th x-direction information, and each of the numbersrespectively corresponding to all the reference pixels is “−1” in the0th y-direction information. Accordingly, the CPU 32 creates thesequence of the numbers “−1, −1, . . . , −1” as the first y-directioninformation. When the CPU 32 creates the second y-direction informationindicated by “(y=2)”, each of the numbers respectively corresponding tothe reference pixels 200, 204, 208 is a negative value in the firstx-direction information, and each of the numbers respectivelycorresponding to the reference pixels 200, 204, 208 is “−1” in the firsty-direction information. Accordingly, the CPU 32 assigns “−1” to each ofthe notable pixels 210, 214, 218 in the second y-direction information.Each of the numbers 202 x, 206 x respectively corresponding to thereference pixels 202, 206 is a positive value in the first x-directioninformation. Accordingly, the CPU 32 assigns “0” as the numbers 212 y,216 y respectively corresponding to the notable pixels 212, 216 in thesecond y-direction information.

As in the above-described case, the CPU 32 creates the third y-directioninformation. In this case, each of the numbers 216 xa respectivelycorresponding to reference pixels 216 a is a positive value in thesecond x-direction information. Accordingly, the CPU 32 assigns “0” aseach of the numbers 220 respectively corresponding to notable pixelscontiguous to the respective reference pixels 216 a in the thirdy-direction information. In the second x-direction information, each ofthe numbers 212 x, 216 xb respectively corresponding to the referencepixels 212, 216 b is a negative value. In the second y-directioninformation, each of the numbers 212 y, 216 y respectively correspondingto the reference pixels 212, 216 b is “0”. Accordingly, the CPU 32assigns “1”, which is obtained by adding one to “0”, as each of thenumbers 222, 224 respectively corresponding to notable pixels contiguousto the respective reference pixels 212, 216 b in the third y-directioninformation. As in the above-described case, the CPU 32 creates thefourth and subsequent y-direction information.

At S116 in FIG. 3, the CPU 32 deletes the m−1th x-direction informationand the m−1th y-direction information from the first working area. Thisprocessing enables the CPU 32 to execute processings at S120 andsubsequent steps with a small memory usage amount. In a modification,the CPU 32 may execute the processing at S112 so as to overwrite them−1th y-direction information with the mth y-direction information. Inthis case, writing of the mth y-direction information and deletion ofthe m−1th y-direction information are executed at the same time. Inanother modification, the CPU 32 may not execute the processing at S116just after the processing at S112. For example, when an amount ofavailable space in the first working area becomes less than a thresholdvalue, unnecessary information may be deleted from the first workingarea. That is, when the CPU 32 writes the mth information (i.e., thex-direction information and the y-direction information) into the firstworking area, the CPU 32 may not delete the m−1th information from thefirst working area.

At S120, the CPU 32 uses the mth x-direction information to determinewhether the mth binary line includes an ON pixel group for whichprocessings at S130-S134 have not been executed yet. Here, the ON pixelgroup is one or more ON pixels contiguous to each other. In the examplein FIG. 6, the 0th binary line is constituted only by the OFF pixels.Thus, the CPU 32 uses the 0th x-direction information to determine thatthere is no ON pixel group in the 0th binary line (S120: NO), this flowgoes to S140. The first binary line includes the two ON pixel groups202, 206. Thus, when the CPU 32 uses the first x-direction informationto determine the first binary line includes the ON pixel group 206 thathas not been processed yet (S120: YES), the CPU 32 identifies the ONpixel group 206 as the pixel group to be processed, and this flow goesto S130. In this explanation, the CPU 32 identifies the unprocessed ONpixel groups in order from the left side toward the right side in themth binary line.

At S130, the CPU 32 uses the mth y-direction information to determinewhether the ON pixel group to be processed is contiguous to any ofanalyzed objects. The analyzed objects are the ON pixel groups in the0th to m−1th binary lines which have been analyzed as objects in theprocessings at S132 or S134 which will be described below. Specifically,the CPU 32 identifies, from the mth y-direction information, each of thenumbers corresponding to the ON pixel group to be processed. When noneof the identified numbers is “0”, the CPU 32 determines that the ONpixel group to be processed is not contiguous to any of analyzed objects(S130: NO), and this flow goes to S132. When any of the identifiednumbers is “0”, the CPU 32 determines that the ON pixel group to beprocessed is contiguous to any of analyzed objects (S130: YES), and thisflow goes to S134.

For example, in the case where the ON pixel group 206 in the firstbinary line in FIG. 6 is a group to be processed, each of the numberscorresponding to the ON pixel group 206 is “−1” in the first y-directioninformation. In this case, a negative decision (NO) is made at S130, andthis flow goes to S132. In the case where the ON pixel group 216 a inthe second binary line is a group to be processed, each of the numbers216 y corresponding to the ON pixel group 216 a is “0” in the secondy-direction information. In this case, a positive decision (YES) is madeat S130, this flow goes to S134.

At S132, the CPU 32 creates new object data in the second working area(see FIG. 4 which will be described below). At S134, the CPU 32 updatesthe object data stored in the second working area (see FIG. 5 which willbe described below). When the processing at S132 or S134 is finished,this flow returns to S120. For example, after the ON pixel group 206 inthe first binary line in FIG. 6 is identified as a group to beprocessed, and then the processing at S132 is finished, the CPU 32 atS120 identifies the ON pixel group 202 as a group to be processed. Whenthe processing at S132 is finished for the ON pixel group 202, anegative decision (NO) is made at S120, and this flow goes to S140.

At S140, the CPU 32 determines whether the current value of the pointerm is the maximum value. The maximum value is the number of pixels in thescan data in the y direction. When the CPU 32 determines that thecurrent value of the pointer m is not the maximum value (S140: NO), theCPU 32 at S142 adds one to the current value of the pointer m and writesa new reading line into the first working area, and this flow returns toS102. When the CPU 32 determines that the current value of the pointer mis the maximum value (S140: YES), this flow goes to S150.

At S150, the CPU 32 determines whether one or more object data createdat S132 and S134 include object data for which a processing at S152 hasnot been executed yet. When the CPU 32 determines that one or moreobject data created at S132 and S134 include object data for which theprocessing at S152 has not been executed (S150: YES), the CPU 32 at S152sets a large-size flag for the object data, and this flow returns toS150. When the CPU 32 determines that one or more object data created atS132 and S134 include no object data for which the processing at S152has not been executed (S150: NO), the first analyzing process (theprocess at S20 in FIG. 2) ends.

There will be next explained, with reference to FIG. 4, a process forcreating new object data at S132 in FIG. 3. The object data representsan object constituted by one or more ON pixels contiguous to each other.As illustrated in FIG. 6, the object data is created by associating thelabel value, coordinates, a width, a height, and a nearby-object flagwith each other. The label value is for labeling (identifying) theobject. The coordinates of the object data indicate the coordinates ofan upper left corner of a rectangular shape circumscribing the object.The width and the height of the object data respectively indicate thenumber of pixels in the circumscribed rectangular shape in the xdirection and the number of pixels in the circumscribed rectangularshape in the y direction. The nearby-object flag indicates one of “ON”and “OFF”. The ON state of the nearby-object flag indicates that thereis another object or other objects in a predetermined region partlysurrounding the object. The OFF state of the nearby-object flagindicates that there is no object in the predetermined region.

The flow in FIG. 4 begins with S200 at which the CPU 32 adds one to thelargest label value among the label values written in the firstanalyzing process and writes an obtained new label value into the secondworking area. For example, in the case where the ON pixel group 206 inFIG. 6 is a group to be processed, the CPU 32 writes the label value “1”into the second working area.

At S210, the CPU 32 writes the coordinates of the leftmost one of the ONpixels of the ON pixel group to be processed, into the second workingarea in association with the label value written at S200. For example,in the case where the ON pixel group 206 in FIG. 6 is a group to beprocessed, the CPU 32 writes the coordinates (5, 1) of the leftmostpixel into the second working area.

At S212, the CPU 32 writes the width and the height of the ON pixelgroup to be processed into the second working area in association withthe label value written at S200. Here, the height is “1”. The width isequal to the number of pixels of the ON pixel group to be processed andis acquired from the mth x-direction information. For example, in thecase where the ON pixel group 206 in FIG. 6 is a group to be processed,the width “6” of the ON pixel group 206 is acquired from the number 206x corresponding to the ON pixel group 206 in the first x-directioninformation.

At S220, the CPU 32 determines whether there is another object in thepredetermined region partly surrounding the leftmost pixel (i.e., an ONpixel not contiguous to the ON pixel group to be processed). In the xdirection, the predetermined region extends rightward from the leftmostpixel by the distance corresponding to twenty pixels and leftward fromthe leftmost pixel by the distance corresponding to twenty pixels. Inthe y direction, the predetermined region extends upward from theleftmost pixel by a distance corresponding to the twenty pixels but doesnot extend downward from the leftmost pixel. For example, in the casewhere a pixel 400 in FIG. 7 is the leftmost pixel, a hatched region isthe predetermined region. In a modification, a value different fromtwenty pixels may be used. For example, in the case where a document isread at a resolution of 300 dpi, 60 pixels may be used.

Specifically, at S220, the CPU 32 first uses the mth x-directioninformation to determine whether there is another object in a regionextending rightward from the leftmost pixel by the distancecorresponding to twenty pixels and leftward from the leftmost pixel bythe distance corresponding to twenty pixels. For example, in the casewhere the ON pixel group 206 in FIG. 6 is a group to be processed, theCPU 32 uses the first x-direction information to determine that thethree ON pixels 202 (i.e., the pixels corresponding to the respectivenumbers 202 x) are present in a region extending rightward from theleftmost pixel (i.e., the pixel corresponding to the number “6”) by thedistance corresponding to twenty pixels (S220: YES). Furthermore, theCPU 32 uses the mth y-direction information to determine whether thereis another object in a region extending upward from the leftmost pixelby the distance corresponding to twenty pixels. For example, in the casewhere the ON pixel group 230 in FIG. 6 is a group to be processed, theCPU 32 uses the ninth y-direction information to determine that the ONpixels 216 a and other ON pixels (i.e., the pixels corresponding to thenumbers “6” and “7”) are present in a region extending upward from theleftmost pixel (i.e., the pixel corresponding to the number “10”) by thedistance corresponding to twenty pixels (S220: YES). In the presentembodiment, the 0th, i.e., the m−1th x-direction information andy-direction information are deleted from the first working area at S116.Thus, the CPU 32 executes the above-described determination using themth x-direction information and y-direction information in the state inwhich the m−1th x-direction information and y-direction information aredeleted from the first working area and in the state in which the first,i.e., the mth x-direction information and y-direction information arewritten in the first working area. This enables the CPU 32 to executethe above-described determination with a small memory usage amount. In amodification, the pixel used as a reference of the predetermined regionat S220 may not be the leftmost pixel. Other examples of the pixel usedas the reference include a central pixel and rightmost pixel in the ONpixel group to be processed.

When the CPU 32 determines that there is another object in thepredetermined region (S220: YES), the CPU 32 at S222 writes “ON” as thenearby-object flag in association with the label value written at S200.When the CPU 32 determines that there is no object in the predeterminedregion (S220: NO), the CPU 32 at S224 writes “OFF” as the nearby-objectflag in association with the label value written at S200. As a result ofthe processing at S222 or S224, new object data is finished, and theprocess in FIG. 4 ends. For example, in the case where the ON pixelgroup 206 in FIG. 6 is a group to be processed, new object data 300 isfinished, and in the case where the ON pixel group 202 is a group to beprocessed, new object data 310 is finished.

There will be next explained, with reference to FIG. 5, a process forupdating the object data at S134 in FIG. 3.

At S240, the CPU 32 identifies object data to be updated. As describedabove, in the case where the ON pixel group 216 a in FIG. 6 is a groupto be processed, for example, the CPU 32 determines that the ON pixelgroup 216 a is contiguous to the analyzed object (S130 in FIG. 3: YES).In this case, the CPU 32 identifies the coordinates of at least onepixel (e.g., (7, 1)) located on the upper side of the ON pixel group 216a so as to be contiguous thereto. The CPU 32 uses the coordinates (5,1), the width “6”, and the height “1” contained in the object data 300in the second working area to identify the inside of the rectangularshape circumscribing the object represented by the object data 300(i.e., the ON pixel group 206). Since the identified coordinates (7, 1)are located in the identified circumscribed rectangular shape, the CPU32 identifies the object data 300 as data to be updated. It is notedthat in the case where there are a plurality of object data in thesecond working area, the CPU 32 identifies circumscribed rectangularshapes respectively for the plurality of object data and identifiesobject data to be updated by checking which circumscribed rectangularshape the identified coordinates are located in.

At S250, the CPU 32 identifies a new circumscribed rectangular shapeusing (i) the circumscribed rectangular shape identified based on theobject data to be updated and (ii) the ON pixel group to be processed.For example, in the case where the ON pixel group 216 a in FIG. 6 is agroup to be processed, the CPU 32 identifies a new circumscribedrectangular shape 250. In the case where the coordinates contained inthe object data to be updated are identical to the coordinates of theupper left corner of the new circumscribed rectangular shape, the CPU 32updates the former coordinates to the latter coordinates. For example,in the case where the ON pixel group 216 a in FIG. 6 is a group to beprocessed, the coordinates of the upper left corner of the newcircumscribed rectangular shape 250 are identical to the coordinates(5, 1) contained in the object data 310 to be updated. In this case, theCPU 32 does not update the coordinates.

At S252, when the width contained in the object data to be updated isnot equal to that of the new circumscribed rectangular shape identifiedat S250, the CPU 32 updates the former width to the latter width.Furthermore, the CPU 32 updates the height contained in the object datato be updated to a new height obtained by adding one to the heightcontained in the object data to be updated. For example, in the casewhere the object data 300 is data to be updated, the CPU 32 updates theheight “1” to the height “2”.

At S260, the CPU 32 determines whether the nearby-object flag containedin the object data to be updated is “OFF”. When the CPU 32 determinesthat the nearby-object flag is “OFF” (S260: YES), this flow goes toS270. When the CPU 32 determines that the nearby-object flag is “ON”(S260: NO), the flow in FIG. 5 ends by skipping S270 and S272. This isbecause it has been determined that another object is present in thepredetermined region partly surrounding the object, and accordinglyprocessings at S270 and S272 need not be executed.

The processing at S270 is similar to the processing at S220. When theCPU 32 determines that there is another object in the predeterminedregion (S270: YES), this flow goes to S272 at which the CPU 32 updatesthe nearby-object flag contained in the object data to be updated, from“OFF” to “ON”. When the processing at S272 is finished, the flow in FIG.5 ends. When the CPU 32 determines that there is no object in thepredetermined region (S270: NO), this flow ends by skipping S272.

By executing the processes in FIGS. 4 and 5, the CPU 32 creates objectdata 302 representing an object constituted by the ON pixel groups 206,216 a in the example in FIG. 6. Also, the CPU 32 creates (i) the objectdata 310 representing the object constituted by the ON pixel group 202and (ii) object data 320 representing an object constituted by the ONpixel group 230.

There will be next explained the processing at S152 in FIG. 3 in detail.At S152, the CPU 32 sets the large-size flag for the object data.Specifically, in the case where at least one of the width and the heightcontained in the object data is equal to or more than a distancecorresponding to four pixels, the CPU 32 sets “ON” as the large-sizeflag for the object data. In the case where each of the width and theheight contained in the object data is less than the distancecorresponding to four pixels, the CPU 32 sets “OFF” as the large-sizeflag for the object data. In the example in FIG. 6, the CPU 32 sets “ON”as the large-size flag for each of the object data 302, 320 and sets“OFF” as the large-size flag for the object data 310. In a modification,a threshold value different from four pixels may be used. For example,in the case where a document is read at a resolution of 300 dpi, twelvepixels may be used as the threshold value.

There will be next explained, with reference to FIG. 3, the secondanalyzing process executed at S30 in FIG. 2. The second analyzingprocess is similar to the first analyzing process except for aprocessing in which the CPU 32 sequentially analyzes the reading linesconstituting the scan data in a direction directed from the lower sidetoward the upper side in the y direction. The following description willbe provided, focusing on the differences from the first analyzingprocess.

At S100, the CPU 32 identifies the lowest reading line in the ydirection as the 0th reading line. At S142, the CPU 32 sequentiallyidentifies the reading lines, each as a new reading line, in order fromthe lower side toward the upper side in the y direction. The mthy-direction information created at S112 represents, for each of thepixels contained in the mth binary line, a distance (i.e., the number ofpixels) between the pixel and the ON pixel located nearest to the pixelamong the ON pixels located on a lower side of the pixel in the ydirection. At S220 in FIG. 4 and S270 in FIG. 5, the predeterminedregion extends downward from the leftmost pixel by the distancecorresponding to twenty pixels in the y direction and does not extendupward from the leftmost pixel.

FIG. 7 is one example of the results of the first analyzing process andthe second analyzing process. In this example, the alphabet “i” isexpressed by the one ON pixel 400 and five ON pixels 402 contiguous toeach other. In the first analyzing process, the CPU 32 sequentiallyanalyzes the reading lines in order from the upper side toward the lowerside in the y direction and creates object data 410 corresponding to theON pixel 400 and object data 420 corresponding to the five ON pixels402. When creating the object data 410, the CPU 32 determines whetherthere is another object (i.e., an ON pixel) in the predetermined region(i.e., the hatched region) located on the upper side of the ON pixel 400(at S220 in FIG. 4). In this example, the CPU 32 determines that thereis no other objects (S220: NO), and the CPU 32 at S224 writes “OFF” asthe nearby-object flag. Also, the CPU 32 writes “OFF” as the large-sizeflag (at S152 in FIG. 3). If the scanner is configured to execute onlythe first analyzing process without executing the second analyzingprocess, the scanner only recognizes, based on the object data 410, thatno object exists near a subject object constituted by the ON pixel 400and that the subject object is of a small size. Thus, the scanner mayidentify the subject object as an isolated point and delete a portion ofthe alphabet “i” from the scan data. That is, the object not to bedeleted may be deleted.

In the present embodiment, in contrast, the CPU 32 in the secondanalyzing process sequentially analyzes the reading lines in order fromthe lower side toward the upper side in the y direction and createsobject data 430 corresponding to the five ON pixels 402 and object data440 corresponding to the ON pixel 400. When creating the object data440, the CPU 32 determines whether there is another object in thepredetermined region (i.e., the hatched region) located on the lowerside of the ON pixel 400 (at S220 in FIG. 4). In this example, since theCPU 32 determines that there is another object (i.e., the ON pixels 402)(S220: YES), the CPU 32 at S222 writes “ON” as the nearby-object flag.Based on the object data 430, the CPU 32 recognizes that there isanother object near the subject object constituted by the ON pixel 400.Accordingly, it is possible to prevent the CPU 32 from identifying thesubject object as the isolated point. That is, it is possible to preventdeletion of the object not to be deleted.

There will be next explained the identification process at S40 in FIG. 2in detail. In the identification process at S40, the CPU 32 uses theresults of the first analyzing process at S20 and the second analyzingprocess at S30 to identify the isolated point. Specifically, the CPU 32identifies object data containing the nearby-object flag being in theOFF state and the large-size flag being in the OFF state, from among oneor more object data obtained in the first analyzing process. It is notedthat such object data will be hereinafter referred to as “first notabledata”. The CPU 32 then identifies object data containing informationthat matches the coordinates, the width, and the height contained in thefirst notable data, from among one or more object data obtained in thesecond analyzing process. It is noted that such object data will behereinafter referred to as “second notable data”. When the nearby-objectflag contained in the second notable data is “OFF”, the CPU 32identifies the object represented by the first notable data (i.e., theobject represented by the second notable data) as the isolated point.

FIG. 8 illustrates one example of the results of the first analyzingprocess and the second analyzing process. An object 450 is an isolatedpoint, objects 460, 470 are the alphabet “i”, and an object 480 is thealphabet “A”. In this example, the CPU 32 first identifies, based on theresult of the first analyzing process, first notable data 450 a, 460 arespectively corresponding to the objects 450, 460. The CPU 32 thenidentifies, based on the result of the second analyzing process, secondnotable data 450 b containing information that matches the coordinates,the width, and the height contained in the first notable data 450 acorresponding to the object 450. Since the nearby-object flag containedin the second notable data 450 b corresponding to the object 450 is“OFF”, the CPU 32 identifies the object 450 as the isolated point. TheCPU 32 identifies, based on the result of the second analyzing process,second notable data 460 b containing information that matches thecoordinates, the width, and the height contained in the first notabledata 460 a corresponding to the object 460. Since the nearby-object flagcontained in the second notable data 460 b corresponding to the object460 is “ON”, the CPU 32 does not identify the object 460 as the isolatedpoint but identifies the object 460 as an object constituting a portionof a character, a drawing, a photograph, or the like. This processingprevents the CPU 32 from deleting the object 460 that constitutes aportion of the alphabet “i”. In the result of the first analyzingprocess, the large-size flag is “ON” in each of object data 470 a, 480 brespectively corresponding to the objects 470, 480. Accordingly, the CPU32 does not identify each of the objects 470, 480 as the isolated pointbut identifies each of the objects 470, 480 as an object such as acharacter, a drawing, a photograph, or the like. This processingprevents the CPU 32 from deleting the objects 470, 480 not to bedeleted. In the present embodiment, the CPU 32 appropriately identifiesa type of the object (i.e., the isolated point, an object constituting aportion of a character or the like, or an object such as a character)and appropriately deletes the object to be deleted.

There will be next explained the correcting process at S50 in FIG. 2 indetail. At S50, the CPU 32 identifies the rectangular shapecircumscribing the object identified as the isolated point at S40, basedon the coordinates, the width, and the height contained in the objectdata corresponding to the object. The CPU 32 then creates one or morereading lines by decompressing one or more compressed lines containingthe region in the identified circumscribed rectangular shape in thecompressed scan data. The CPU 32 corrects each of one or more pixelscorresponding to the identified region among pixels constituting thecreated one or more reading lines, to a pixel having a pixel value of awhite color (R=G=B=255). This processing deletes the isolated point. Ina modification, the CPU 32 may calculate a pixel value, which representsa background color of scanned image, using a well-known technique andcorrect the pixel to a pixel having the calculated pixel value.

Effects in First Embodiment

In the present embodiment, the scanner 10 creates the mth y-directioninformation at S112 in FIG. 3. Thus, the scanner 10 may use the createdmth y-direction information to determine whether there is another ONpixel not contiguous to the ON pixel group, in the predetermined regionpartly surrounding the ON pixel group to be processed (S220 in FIG. 4,S270 in FIG. 5). Accordingly, the scanner 10 executes theabove-described determination without the need to use each of binarylines located on an upper side of the mth binary line. That is, thescanner 10 executes the above-described determination in the firstanalyzing process using the mth binary line written in the working area38 in the state in which each of binary lines located on an upper sideof the mth binary line is not written in the working area 38. Thisprocessing enables the scanner 10 to execute the above-describeddetermination with a small memory usage amount.

In the processing at S220 in FIG. 4 or S270 in FIG. 5 in the firstanalyzing process (S20 in FIG. 2), the scanner 10 determines whetherthere is another ON pixel not contiguous to the ON pixel group, in thepredetermined region partly surrounding the ON pixel group to beprocessed. This determination is executed without using binary lineslocated on a lower side of the mth binary line. That is, thisdetermination is executed in the state in which the binary lines are notwritten in the working area 38. Also, in the processing at S220 in FIG.4 or S270 in FIG. 5 in the second analyzing process (S30 in FIG. 2), thescanner 10 executes the above-described determination without usingbinary lines located on an upper side of the mth binary line. That is,the scanner 10 executes the above-described determination in the statein which the binary lines are not written in the working area 38. Thisprocessing enables the scanner 10 to execute the above-describeddetermination with a small memory usage amount.

There will be next explained association of components. The scanner 10is one example of an image analyzing apparatus. The first working areain the working area 38 is one example of a first specific area, and thesecond working area in the working area 38 is one example of a secondspecific area. The y direction is one example of a first direction, andthe x direction is one example of a second direction. The upper side isone example of a first side, and the lower side is one example of asecond side. The compressed scan data is one example of read image data.The binary lines are one example of a plurality of line pixel groups.The ON pixel is one example of a first-type pixel. The OFF pixel is oneexample of a second-type pixel. The x-direction information is oneexample of pixel information. The y-direction information created in thefirst analyzing process is one example of first distance information.The y-direction information created in the second analyzing process isone example of second distance information. The ON pixel group 206 inFIG. 6 is one example of a first subject group, and the ON pixel group216 a in FIG. 6 is one example of a second subject group. Thepredetermined region (i.e., the hatched region) used in the firstanalyzing process in FIG. 7 is one example of a first region. Thepredetermined region (i.e., the hatched region) used in the secondanalyzing process in FIG. 7 is one example of a second region. Thecorrecting process at S50 in FIG. 2 is one example of a first process.Each of the coordinates, the width, and the height contained in theobject data is one example of particular information. The nearby-objectflag contained in the object data is one example of result information.

Second Embodiment

Before explaining a second embodiment, processings in a comparativeexample will be explained. FIG. 9 illustrates an object representing acharacter “X”. In the case where the CPU 32 executes the processings atS110-S134 in FIG. 3 for the first binary line, when an ON pixel group500 is identified at S120 as a group to be processed, the CPU 32determines at S220 in FIG. 4 whether there is an ON pixel group 502 in apredetermined region partly surrounding the ON pixel group 500 (S220:YES). Thus, the CPU 32 at S222 creates object data 510 containing thenearby-object flag being in the ON state. When the CPU 32 thereafteridentifies the ON pixel group 502 as a group to be processed at S120, inFIG. 3, the CPU 32 at S220 in FIG. 4 determines that the ON pixel group500 is present in the predetermined region partly surrounding the ONpixel group 502 (S220: YES). Thus, the CPU 32 at S222 creates objectdata 512 including the nearby-object flag being in the ON state.

In the case where the CPU 32 thereafter executes the processings atS110-S134 in FIG. 3 for the second binary line, when an ON pixel group504 is identified at S120 as a group to be processed, the CPU 32 at S130determines that the ON pixel group 504 is contiguous to both of the ONpixel groups 500, 502. That is, the CPU 32 determines that the ON pixelgroups 500-504 constitute the same object, i.e., the character “X”. Inthis case, it is considered that the object data 510, 512 are integratedinto object data 514 corresponding to one object. Since thenearby-object flag is “ON” for each of the object data 510, 512, the CPU32 writes “ON” as the nearby-object flag for the object data 514. Thatis, the CPU 32 writes “ON” as the nearby-object flag though there is noobject around the object in reality. In this case, the CPU 32 cannotappropriately identify the type of the object (i.e., the isolated point,an object constituting a portion of a character or the like, or anobject such as a character).

To appropriately identify the type of the object, the second embodimentis different from the first embodiment in the predetermined region usedat S220 in FIG. 4 and S270 in FIG. 5. That is, as illustrated in FIG. 9,the predetermined region (i.e., the hatched region) used in the firstanalyzing process does not include a region extending from the leftmostpixel in each of the up, right, and left directions by a distancecorresponding to four pixels. Though not illustrated, the predeterminedregion used in the second analyzing process does not include a regionextending from the leftmost pixel in each of the down, right, and leftdirections by a distance corresponding to four pixels. That is, thepredetermined region does not contain a region located within a distancecorresponding to four pixels from the leftmost pixel and contain aregion located outside a distance corresponding to four pixels from theleftmost pixel and within the distance corresponding to twenty pixelsfrom the leftmost pixel. In a modification, a threshold, value differentfrom four pixels may be used. In the case where a document is read at aresolution of 300 dpi, twelve pixels may be used as the threshold value.

In the present embodiment, four pixels located on the right side of theON pixel group 500 are excluded from the predetermined region. Thus, theCPU 32 at S220 in FIG. 4 determines that there is no ON pixel groupwithin the predetermined region partly surrounding the ON pixel group500 (S220: NO), and the CPU 32 at S222 creates object data 520containing the nearby-object flag being in the “OFF” state. Also, fourpixels located on the left side of the ON pixel group 502 are excludedfrom the predetermined region. Thus, the CPU 32 at S220 determines thatthere is no ON pixel group within the predetermined region partlysurrounding the ON pixel group 502 (S220: NO), and the CPU 32 at S222creates object data 522 containing the nearby-object flag being in the“OFF” state. That is, it is possible to prevent the CPU 32 fromdetermining that one of the ON pixel groups 500, 502 constituting thesame object is present near the other of the ON pixel groups 500, 502.Thereafter, the CPU 32 at S130 in FIG. 3 determines that the ON pixelgroup 504 is contiguous to both of the ON pixel groups 500, 502 and atS240-S252 in FIG. 5 integrates the object data 520, 522 into object data524. Since the nearby-object flag is “OFF” in the object data 520, 522,the CPU 32 appropriately writes “OFF” as the nearby-object flag also forthe object data 524.

In the present embodiment, the nearby-object flag is appropriatelywritten, thereby appropriately identifying the type of the object (i.e.,the isolated point, an object constituting a portion of a character orthe like, or an object such as a character). In the present embodiment,the leftmost pixel of the ON pixel group to be processed is one exampleof a subject pixel. The four pixels are one example of a firstparticular distance, and the twenty pixels are one example of a secondparticular distance.

Third Embodiment

As in the second embodiment, in the present embodiment, as illustratedin FIG. 10, the predetermined region (i.e., the hatched region) used atS220 in FIG. 4 and S270 in FIG. 5 does not contain a region locatedwithin a distance corresponding to four pixels from the leftmost pixeland contains a region located outside a distance corresponding to fourpixels from the leftmost pixel and within the distance corresponding totwenty pixels from the leftmost pixel. In the example in FIG. 10, thereare ON pixels 600, 602 on an upper side of the leftmost pixel. In thiscase, the 22nd y-direction information contains, as the numbercorresponding to the leftmost pixel, “2” that is a distance between theleftmost pixel and the ON pixel 600. That is, the 22nd y-directioninformation does not contain information about the ON pixel 602. As aresult, if the CPU 32 executes the determination at S220 and S270 usingonly the 22nd y-direction information, the CPU 32 determines that thereis no ON pixel in the predetermined region because the ON pixel 600 isnot contained in the predetermined region, and the CPU 32 does notrecognize the ON pixel 602. That is, the CPU 32 executes wrongdetermination though the ON pixel 602 is contained in the predeterminedregion in reality.

In the present embodiment, the CPU 32 creates subsidiary information atS114 in FIG. 3 to avoid the above-described wrong determination. Here,the subsidiary information is m−4th y-direction information. The “4”represents the number of pixels partly surrounding the leftmost pixeland excluded from the predetermined region. Specifically, the CPU 32 atS114 uses the m−4th binary line as in the processings at S102-S112 tocreate m−4th x-direction information and the subsidiary information,i.e., the m−4th y-direction information. In particular, the CPU 32 usesthe m−5th x-direction information and the m−5th y-direction informationto create the subsidiary information, i.e., the m−4th y-directioninformation.

At S220 in FIG. 4 and S270 in FIG. 5, the CPU 32 uses the subsidiaryinformation, i.e., the m−4th y-direction information to determinewhether there is an ON pixel in the predetermined region located on anupper side of the leftmost pixel. In the example in FIG. 10, the 18thy-direction information as the subsidiary information contains “4”,which is a distance between the OFF pixel 604 and the ON pixel 602, asthe number corresponding to an OFF pixel 604 located at the sameposition as the leftmost pixel in the x direction. Accordingly, use ofthe subsidiary information enables the CPU 32 to appropriately determinethat the ON pixel 602 is present in the predetermined region located onan upper side of the leftmost pixel. In the present embodiment, them−5th x-direction information is one example of k−1th pixel information.The m−5th y-direction information is one example of k−1th first distanceinformation.

While the embodiments have been described above, it is to be understoodthat the disclosure is not limited to the details of the illustratedembodiments, but may be embodied with various changes and modifications,which may occur to those skilled in the art, without departing from thespirit and scope of the disclosure.

In each of the above-described embodiments, the CPU 32 identifies theobject constituting the isolated point at S40 in FIG. 2. In a firstalternative embodiment, the CPU 32 may identify the object constitutingthe character. In this case, a threshold value for distinguishingbetween “ON” and “OFF” of the large-size flag at S152 in FIG. 3 may bethe number of pixels which corresponds to 2 cm. The number of pixelsdepends on a reading resolution. At S40 in FIG. 2, the CPU 32 identifiesobject data containing the large-size flag being in the “OFF” state andcontaining the nearby-object flag being in the “ON” state as a result ofat least one of the first analyzing process and the second analyzingprocess. The character in most cases has a width and a height of lessthan 2 cm. Furthermore, there are usually other characters around thecharacter. Thus, the object data containing the large-size flag being inthe “OFF” state and containing the nearby-object flag being in the “ON”state in most cases represents an object representing the character. AtS50 in FIG. 2, the CPU 32 executes optical character recognition (OCR)for each object identified as a character. That is, the CPU 32 need notexecute OCR for each object not identified as a character, that is, theCPU 32 need not execute OCR for the entire scan image, resulting inhigher speed of OCR. In the present embodiment, the number of pixelswhich corresponds to 2 cm is one example of a second threshold value,and OCR is one example of a first process.

In a second alternative embodiment, the x-direction information may notbe created at S110 in FIG. 3. In this case, the CPU 32 may at S112create the mth y-direction information by using the m−1th binary lineinstead of the m−1th x-direction information. In this second alternativeembodiment, the binary line is one example of the pixel information.

In a third alternative embodiment, the second analyzing process at S30in FIG. 2 may not be executed. In this case, the CPU 32 may at S40identify the object as the isolated point using only the result of thefirst analyzing process.

In a fourth alternative embodiment, in the case where reading isperformed for an image having white characters on solid fill of black,for example, white isolated points different from the white charactersmay be formed on the solid fill of black. To remove the white isolatedpoints, the CPU 32 may at S120 in FIG. 3 identify the OFF pixel group tobe processed and at S220 in FIG. 4 and S270 in FIG. 5 determine whetherthere is another OFF pixel in the predetermined region partlysurrounding the leftmost pixel of the OFF pixel group to be processed.Then, the CPU 32 may at S50 in FIG. 2 correct each of the pixelscorresponding to the object representing the isolated points, to pixelsrepresenting a black color. In the present alternative embodiment, theOFF pixel is one example of the first-type pixel, and the ON pixel isone example of the second-type pixel.

There will be explained a fifth alternative embodiment. For example, asituation in which the scanner reads a document containing onlycharacter strings is assumed. Since there are characters around acertain character in most cases, the CPU 32 does not need the large-sizeflag to identify, as a character, the object corresponding to thenearby-object flag being in the ON state. That is, the CPU 32 does notneed the large-size flag to identify, as an isolated point, the objectcorresponding to the nearby-object flag being in the “OFF” state.Accordingly, the size of the object may not be considered in each of theabove-described first to third embodiments.

In a sixth alternative embodiment, for example, the CPU 32 may at S10 inFIG. 2 execute what is called binary scanning for a document to createcompressed scan representing a binary image constituted by the ON pixelsand the OFF pixels. In the present alternative embodiment, theprocessings at S102 and S104 in FIG. 3.

In a seventh alternative embodiment, each of the processings in FIG. 2may be executed by a scanner driver installed in the PC 50. That is, theimage analyzing apparatus is not limited to the scanner and may be anydevice capable of analyzing an image. Examples of such device includepersonal computers, servers, multi-function peripherals, andsmartphones.

In the above-described embodiments, the CPU 32 of the scanner 10executes the program 36 (i.e., software) to execute the processings inFIGS. 2-10. In an eighth alternative embodiment, at least one of theprocessings in FIGS. 2-10 may be executed by hardware such as a logiccircuit.

The technical components described in the present specification or thedrawings exhibit technical utility alone or in various combinations, andare not limited to the combinations disclosed in the claims at the timeof filing. Furthermore, the techniques illustrated in the presentspecification or the drawings may simultaneously achieve a plurality ofobjects, and have technical utility by achieving one of these objects.Also, the present disclosure may be achieved in other forms such as amethod of analyzing an image.

What is claimed is:
 1. An image analyzing apparatus comprising aprocessor and a memory, the processor configured to perform: acquiringread image data created by reading of a document; executing a firstanalyzing process based on the acquired read image data; storing aresult of the first analyzing process; and executing a correctionprocess based on the result of the first analyzing process stored in thememory, wherein the processor is configured to, in the first analyzingprocess, perform: sequentially identifying a plurality of line pixelgroups from a first side of the acquired read image data toward a secondside of the acquired read image data in a first direction, wherein theplurality of line pixel groups are arranged in the first direction,wherein each of the plurality of line pixel groups comprises a pluralityof pixels arranged in a second direction orthogonal to the firstdirection, wherein each of the plurality of pixels is one of afirst-type pixel and a second-type pixel, wherein the first-type pixelis a pixel representing an object different from a background of thedocument, and the second-type pixel is a pixel representing thebackground of the document; in a case where an m1th line pixel groupamong the plurality of line pixel groups is identified, creating m1thfirst distance information corresponding to the m1th line pixel groupbased on (m1−1)th pixel information stored in the memory andcorresponding to an (m1−1)th line pixel group among the plurality ofline pixel groups; and (m1−1)th first distance information stored in thememory and corresponding to the (m1−1)th line pixel group; and storingthe m1th first distance information into the memory, wherein the pixelinformation for each of the plurality of line pixel groups indicatesthat each of the plurality of pixels constituting said each of theplurality of line pixel groups is one of the first-type pixel and thesecond-type pixel, wherein the first distance information for each ofthe plurality of line pixel groups indicates a distance between eachpixel of the plurality of pixels constituting said each of the pluralityof line pixel groups and the first-type pixel located on the first sideof said each pixel and nearest to said each pixel, wherein m1 is aninteger greater than or equal to two; and in a case where the m1th linepixel group comprises a first subject group constituted by a pluralityof first-type pixels contiguous to each other in the second direction,determining, based on the m1th first distance information stored in thememory, whether at least one first-type pixel not contiguous to theplurality of first-type pixels of the first subject group is present ina first region surrounding the first subject group, and wherein, in acase where the processor determines an absence of the at least onefirst-type pixels in the first region, and in a case where a size of aparticular object that comprises the first subject group in the readimage data is less than a first threshold value, the processor isconfigured to, based on the result of the first analyzing process storedin the memory, identify the particular object as a noise object andexecute the correction process for correcting each pixel of the noiseobject to a pixel representing a background color of the document,wherein the noise object comprises the first subject group and isconstituted by the plurality of the first-type pixels contiguous to eachother, and wherein correcting each pixel of the noise object comprisesassigning a background pixel value to each pixel being corrected.
 2. Theimage analyzing apparatus according to claim 1, wherein the processor isconfigured to, in the first analyzing process, determine whether atleast one first-type pixel is present in the first region surroundingthe first subject group, based on the first distance information for them1th line pixel group stored in the memory, in a state in which thefirst distance information for each line pixel group located on thefirst side of the m1th line pixel group is deleted from a first specificarea in the memory, and the first distance information for the m1th linepixel group is written in the first specific area.
 3. The imageanalyzing apparatus according to claim 1, wherein the processor isconfigured to, in the first analyzing process, perform: identifying the(m1−1)th line pixel group by writing the (m1−1)th line pixel group intoa first specific area in the memory of the image analyzing apparatus;and deleting the (m1−1)th line pixel group from the first specific areabefore writing the m1th line pixel group into the first specific area;creating the m1th first distance information by writing the m1th firstdistance information into the first specific area; and deleting the(m1−1)th first distance information from the first specific area in acase where writing the m1th first distance information into the firstspecific area.
 4. The image analyzing apparatus according to claim 1,wherein the processor is configured to, in the first analyzing process,identify the size of the particular object based on the first subjectgroup, and wherein the processor is configured to execute the correctionprocess for the particular object based on the result of the firstanalyzing process and the size of the particular object.
 5. The imageanalyzing apparatus according to claim 1, wherein the processor isconfigured to determine that the particular object is a character andexecute the correction process as a processing relating to thecharacter, in a case where the processor determines a presence of atleast one first-type pixel is present in the first region and in a casewhere the size of the particular object is less than a second thresholdvalue.
 6. The image analyzing apparatus according to claim 1, whereinthe first region does not comprise a region located within a firstparticular distance from a subject pixel contained in the first subjectgroup and comprises a region located outside the first particulardistance from the subject pixel and within a second particular distancefrom the subject pixel.
 7. The image analyzing apparatus according toclaim 6, wherein the processor is configured to, in a case where them1th line pixel group is identified, create subsidiary information basedon (k−1)th pixel information corresponding to a (k−1)th line pixel groupof the plurality of line pixel groups and on (k−1)th first distanceinformation corresponding to the (k−1)th line pixel group and store thesubsidiary information into the memory, wherein the subsidiaryinformation is kth first distance information corresponding to a kthline pixel group of the plurality of line pixel groups, where k is avalue greater than or equal to two and obtained by subtracting a valuecorresponding to the first particular distance from m1, and wherein theprocessor is configured to determine, based on the m1th first distanceinformation and the kth first distance information, whether the at leastone first-type pixel not contiguous to the plurality of first-typepixels of the first subject group is present in the first regionsurrounding the first subject group.
 8. The image analyzing apparatusaccording to claim 1, wherein the first region does not comprise aregion located on the second side of the first subject group.
 9. Theimage analyzing apparatus according to claim 1, wherein the processor isconfigured to execute a second analyzing process based on the read imagedata, wherein the processor is configured to, in the second analyzingprocess, perform: sequentially identifying the plurality of line pixelgroups from the second side toward the first side in the firstdirection; in a case where an m2th line pixel group among the pluralityof line pixel groups is identified, creating m2th second distanceinformation corresponding to the m2th line pixel group based on (m2−1)thpixel information corresponding to an (m2−1)th line pixel group of theplurality of line pixel groups and on (m2−1)th second distanceinformation corresponding to the (m2−1)th line pixel group and storingthe m2th second distance information into the memory, wherein seconddistance information for each of the plurality of line pixel groupsindicates a distance between each pixel of the plurality of pixelsconstituting said each of the plurality of line pixel groups and thefirst-type pixel located on the second side of said each pixel andnearest to said each pixel, wherein m2 is an integer greater than orequal to two; and in a case where the m2th line pixel group comprisesthe first subject group, determining, based on the m2th second distanceinformation stored in the memory, whether at least one first-type pixelnot contiguous to the plurality of first-type pixels of the firstsubject group is present in a second region surrounding the firstsubject group, and wherein the processor is configured to, based on theresult of the first analyzing process and a result of the secondanalyzing process, execute the correction process for the particularobject.
 10. The image analyzing apparatus according to claim 1, whereinthe processor is configured to, in the first analyzing process, perform:in a case where the m1th line pixel group is identified, storing (i)particular information for identifying a position and a size of theparticular object and (ii) result information indicating a result ofdetermination for the first subject group, into the memory in a state inwhich the particular information and the result information areassociated with each other; in a case where an (m1+1)th line pixel groupamong the plurality of line pixel groups is identified, creating(m1+1)th first distance information corresponding to the (m1+1)th linepixel group based on m1th pixel information corresponding to the m1thline pixel group and on the m1th first distance informationcorresponding to the m1th line pixel group and storing the (m1+1)thfirst distance into the memory; updating the particular information in acase where the (m1+1)th line pixel group comprises a second subjectgroup contiguous to the first subject group and constituted by aplurality of first-type pixels contiguous to each other in the seconddirection each as the first-type pixel; and updating the resultinformation associated with the particular information, in a case wherethe controller determines, in determination for the first subject group,that the at least one first-type pixel is absent in the first region anddetermines, based on the created (m1+1)th first distance information,that at least one first-type pixel is present in the first regionsurrounding the second subject group.
 11. The image analyzing apparatusaccording to claim 1, wherein the processor is further configured to, inthe first analyzing process, perform: identifying the (m1−1)th linepixel group by writing the m1−1th line pixel group into a first specificarea in the memory; deleting the (m1−1)th line pixel group from thefirst specific area before writing the m1th line pixel group into thefirst specific area; creating the m1th first distance information bywriting the m1th first distance information into the first specificarea; deleting the (m1−1)th first distance information from the firstspecific area in a case where the m1th first distance information iswritten into the first specific area; in a case where the m1th linepixel group is identified, storing (i) particular information foridentifying a position and a size of the particular object and (ii)result information indicating a result of determination for the firstsubject group, into a second specific area in the memory in a state inwhich the particular information and the result information areassociated with each other; and deleting the particular information andthe result information from the second specific area after the firstanalyzing process is finished.
 12. A non-transitory storage mediumstoring a plurality of instructions executable by a computer of an imageanalyzing apparatus, the computer comprising a processor and a memory,the plurality of instructions, when executed by the computer, causingthe image analyzing apparatus to perform: acquiring read image datacreated by reading of a document; executing a first analyzing processbased on the acquired read image data; storing a result of the firstanalyzing process in the memory; and executing a correction processbased on a result of the first analyzing process, wherein when executedby the computer, the plurality of instructions cause the image analyzingapparatus to, in the first analyzing process, perform: sequentiallyidentifying a plurality of line pixel groups from a first side of theacquired read image data toward a second side of the acquired read imagedata in a first direction, wherein the plurality of line pixel groupsare arranged in the first direction, wherein each of the plurality ofline pixel groups comprises a plurality of pixels arranged in a seconddirection orthogonal to the first direction, wherein each of theplurality of pixels is one of a first-type pixel and a second-typepixel, wherein the first-type pixel is a pixel representing an objectdifferent from a background of the document, and the second-type pixelis a pixel representing the background of the document; in a case wherean m1th line pixel group among the plurality of line pixel groups isidentified, creating m1th first distance information corresponding tothe m1th line pixel group based on (m1−1)th pixel information stored inthe memory and corresponding to an (m1−1)th line pixel group among theplurality of line pixel groups; and (m1−1)th first distance informationstored in the memory and corresponding to the (m1−1)th line pixel group;and storing the m1th first distance information into the memory, whereinthe pixel information for each of the plurality of line pixel groupsindicates that each of the plurality of pixels constituting said each ofthe plurality of line pixel groups is one of the first-type pixel andthe second-type pixel, wherein the first distance information for eachof the plurality of line pixel groups indicates a distance between eachpixel of the plurality of pixels constituting said each of the pluralityof line pixel groups and the first-type pixel located on the first sideof said each pixel and nearest to said each pixel, wherein m1 is aninteger greater than or equal to two; and in a case where the m1th linepixel group comprises a first subject group constituted by a pluralityof first-type pixels contiguous to each other in the second direction,determining, based on the m1th first distance information stored in thememory, whether at least one first-type pixel not contiguous to theplurality of first-type pixels the first subject group is present in afirst region surrounding the first subject group, and wherein, in a casewhere the processor determines an absence of the at least one first-typepixels in the first region, and in a case where a size of a particularobject that comprises the first subject group in the read image data isless than a first threshold value, the processor is configured to, basedon the result of the first analyzing process stored in the memory,identify the particular object as a noise object and execute thecorrection process for correction each pixel of the noise object to apixel representing a background color of the document, wherein the noiseobject comprises the first subject group and is constituted by theplurality of first-type pixels contiguous to each other, and whereincorrecting each pixel of the noise object comprises assigning abackground pixel value to each pixel being corrected.